Main image of article Everything You Need to Know about A.I.-Assisted Hiring

Breakout tech like ChatGPT proves the sophistication of A.I. and its infiltration across almost all sectors of our lives is growing. It's exciting yet concerning. These uncharted waters, specifically the intersection of A.I. in our personal and professional lives, should stir questions, especially regarding A.I.-assisted hiring. 

For context, I'm a techie, a technical engineer through education and practice, and the CEO of an HR tech company that, you guessed it, supports employers with AI to improve recruiting and hiring. In fact, did you know 1 in 4 organizations use automation and/or AI to support HR-related activities, with 79 percent A.I. usage in recruitment? So, what do you need to know as a job seeker?

First, Let’s Unpack Why Companies Use AI in Hiring

In short, it's all about efficiency, cost savings, and accuracy. The same SHRM research summarized the reasons as follows: 

  • 85 percent for time savings and efficiency 
  • 44 percent improvement in identifying top candidates
  • 30 percent for the reduced bias
  • 18 percent to help find more diverse candidates

What Do Candidates Think?

It depends. Tildo ran a survey and found that 39 percent of job candidates are okay with using A.I., but if a human is involved, the same candidate's approval of A.I. in hiring increased to 75 percent. 

What are General Concerns about A.I.-Assisted Hiring? 

A.I.-assisted hiring is inevitable. What do you, as a job seeker, need to know? Bias. What kinds of bias?
 

Data bias: A.I. is only as good as the data it's trained on, so if the data is biased, everything is biased. For example, if the A.I. is trained on resumes from male candidates, there's likely bias against female candidates. 

Fairness bias: A.I. algorithms can perpetuate existing biases in the hiring process, such as discrimination based on race, gender, age, or socioeconomic status.

Algorithmic bias: Algorithms for A.I. are often designed to optimize specific metrics, such as the number of hires or the time to fill a position, which can lead to biased decisions.

Transparency and ‘explainability’: A.I. models can be challenging to understand, making it hard to identify and address potential biases.

How Can You Prepare for A.I. in the Hiring Process?
 

Tailor your application: Connect with the recruiter on LinkedIn responsible for the role, share your interest in the job, and ask how different qualifications or skills are scored in the A.I. algorithm. Use those exact skills in your application and in your responses.  

Try not to be too niche: You could be at a disadvantage if you have niche experiences that don’t fit within the dataset the A.I. was trained on. This could make it hard for the A.I. to understand your relevance, giving you a lower score. Again, try to match your experience with the skills listed in the job description. 

Avoid vague language and overused terms: Phrases like ‘team player,’ ‘hard worker,’ ‘results-oriented,’ ‘detail-oriented,’ ‘excellent communication skills,’ and ‘self-motivated’ are empty. Backing up the vague terms with specific examples and data points should help the AI better score your experience. 

Avoid being too creative: During the initial screening facilitated by A.I., creativity, use of figurative language or humor could confuse the A.I. algorithm, making it hard to assess your qualifications or abilities. It’s better to stick to plain, concise language.

Network: Reach out to people who work at the company and ask for advice or an introduction to the hiring team.

If you think A.I. has hurt your chances of getting a job, you can file a complaint with the relevant government agency, such as the Equal Employment Opportunity Commission (EEOC) in the United States.

Conclusion

A.I. in hiring is an emerging field; there are lessons to learn for job candidates and hiring teams. As a job candidate, A.I. brings a new opportunity you must embrace. Start by understanding how A.I. works and how to use it, which will undoubtedly become a future skill requirement. Though, I'd caution against applying for a job if a company cannot explain how the A.I. is used or provide transparency.

Satish Kumar is CEO of Glider AI.